Estimation of Power Peaking Factor (PPF)Parameter in VVER Reactor Using Soft Computing, Case Study: Bushehr Nuclear Power Plant

Sharifi, Saeed | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53829 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Ghofrani, Mohammad Bagher; Moshkbar Bakhshayesh, Khalil
  7. Abstract:
  8. operation of a nuclear power plant. Therefore, constant monitoring of the reactor core with reliable methods is important. To monitor the reactor heart, it is necessary to estimate and calculate some parameters, with high speed and accuracy, such as power distribution inside the heart, reactivity feedback coefficients, PPF, DNBR, etc. Analytical methods are often used to calculate these parameters, which in case of failure of the sensors, the calculations will be practically disrupted, and the method used in this research can solve these problems by losing a small amount of accuracy.In this study using real data of Bushehr nuclear power plant (BNPP) and by soft computing methods and without using the data of self-powered neutron detectors (SPNDs), the maximum linear heat rate of BNPP is estimated. The efficient learning algorithms ofartificial neural network (ANN) including Levenberg-Marquardt (LM)and Bayesian regularization (BR)in combination with different features selection techniques including Pearson, Spearman, and Kendall’s tau are employed to estimate the target parameter. Results show that the proposed method is appropriate for estimation of the maximum linear heat rate. Given the importance of this parameter in terms of safety and the fact that its excessive increase actuates the shutdown signal of the reactor, use of the appropriated approaches such as the present study, can increase the safety of the plant and improve Defense-In-Depth (DID).Also, one of the characteristics of this research is the study of network performance by creating noise in the input data and also the use of real data of Bushehr power plant in order to obtain practical result.In this research, the parameter which is one of the most important parameters of the reactor and one of the power peaking factors, was calculated with good accuracy and AMRE error reached 0.0049 and CDF 99% of the data reached 0.0345 which is an acceptable result compared to other researchs. The use of feature selection technique in this study increased the accuracy and also reduced the computational load
  9. Keywords:
  10. Parameter Estimation ; Nuclear Power Plants ; Feature Selection ; Power Peaking Factor ; Correlation Coefficient ; Soft Computation ; Nuclear Safety

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